Data marts. Intensive care experience

Vitaly Herasevich, MD, PhD, MSc

Assistant Professor of Medicine and Anesthesiology,Department of Anesthesiology,Multidisciplinary Epidemiology and Translational Research in Intensive Care (M.E.T.R.I.C.)

herasevich.vitaly@mayo.eduJun 2012

Why we need Datamart?

April 2011 56 Hospitals worldwide

Including Mayo Clinic

©2011 MFMER | slide-4

http://mayoweb.mayo.edu/it-operations/supported-systems.html

EHR

Data volume before and in ICU

Microbiology, labs, medications, chest X-ray, Nurses flowsheet, Clinical notes (history and impression/plan) – Vitals excluded

“Datapoints” in acute setting

Routine noninvasive monitoring

• EKG• Arterial blood pressure• Heart rate• Respiratory rate• Temperature

Fluid balance

• Fluid IN• Fluid OUT• Urine output

Laboratory blood

• Hemoglobin• Serum electrolytes• Blood chemistry

Invasive hemodynamic monitoring

• Central venous pressure• Arterial blood gases and pH• Pulmonary arterial pressure• Oxygen transport variables• Intra-arterial blood pressure

Natural contexts

• Demographic data• Chronic diseases history• Allergies• Stress• Pain

Tissue perfusion / oxygenation monitoring

• Pulse oximetry• Transcutaneous oxygen and carbon dioxide monitoring

Ventilator monitoring

• FiO2

• PIP• PEEP/CPAP• Mean Airway Pressure• Tidal Volume

Brain function monitoring

• Electroencephalography• Intracranial pressure

Routine cardiac monitoring

• Cardiac output • Hemodynamic variables• Blood volume• Colloidal osmotic pressure

Average data points per dayPer Patient Per 24 bedded ICU

Labs 60 1440Drug Orders 10 240Microbiology 2 48X ray 2 48Vitals 1950 46800

FOCUS ON TOPIC OF INTEREST

ICU Datamart (METRIC Datamart)

Radiology Reports

RIMS

Nursing Flow Sheet

MICS Lastword

Clinical notes

MCLS Lastword

APACHE

APACHE

Historical

REP

CPOE

Enterprise orders

ICD-9

DSS

Past history

PPI

OR Data mart

HL7

Microbiology Reports

HRBS

Labs

HRBS

Monitored data

Chart+

Transfusion Orders

MYSIS

Drug orders

HRBS

ICU demographics

HRBS

Fluids: in/out

Chart+

Emergency acute area

YES

Surgical schedule

Surgical

ICU Data mart

SQL sto

red p

roce

dures

SQ

L sto

red p

roced

ures

Key Facts

• ~ 15,000 admissions per year• ~ 1,000,000 vital records per week• Data available from 2003• Updated every hour in average (15 min for vitals)• Near real-time• ED critical area

Anesthesia Datamart (OR Datamart)

Anesthesia locations included in OR Data mart

©2011 MFMER | slide-14

Available data (Apr 2012)

1998 ….. 2012 Yearly average Monthly average

Total1998-2011

Demographics 750,000 65,000 5,400,000

Events 20,000,000 1,600,000 144,000,000

Procedures 300,000 26,000 2,500,000

Fluids 7,900,000 650,000 87,000,000

OR Medications 5,000,000 400,000 50,000,000

Vital signs 190,000,000 16,000,000 1,600,000,000

Documents 3,200,000 250,000 27,300,000

Procedures 330,000 28,000 2,500,000

Teams 620,000 50,000 4,600,000

Near real time (5 min delay)

Approach

Rule one: lego bricks

Rule two: UNIX- no user interface• No formal web/query Interface• ODBC connection allows query from any app (JMP, Excel, SAS…)

Rule three: raw data

Approach: technically• SQL server with institutional support

• Tables divided by years

• In “Current tables” only patients who in currently in anesthesia location or ICU

• EAV (entity – attribute – value) structure

• Continuously “Testing – production”

• Test –> production DBs

Real time monitoringStatistical control

Currently: no institutional 24/7 support

Data integrity

Herasevich V, Pickering BW, Dong Y, et al. Informatics infrastructure for syndrome surveillance, decision support, reporting, and modeling of critical illness. Mayo Clin Proc 2010;85(3):247-254. (PMID: 20194152)

Herasevich V, Kor D, Li M, et al. ICU Data Mart: A Non-IT Approach. Healthcare Informatics 2011;28(11):42-45. (PMID: pending)

Areas of implementation

APACHE replacement

Reports1994 - 2009

APACHE replacement project

APACHE IV

Free text search for medical admission diagnoses

Clinical reports

Effective management

Joint Commission on Healthcare Organizations (JCAHO) measurement

of ICU performance.• Mortality report

• Length of Stay Review

• ICU Death Review

• ICU admission Low Risk Monitor Review

• ICU Readmission Review

METRIC Reports

• Monthly reports• Ad-hock reports• Customized reports

1. Hospital Length of Stay for ICU Graduates – Unadjusted

2. ICU Length of Stay – Unadjusted

3. ICU Length of Stay – Adjusted

4. ICU Readmission Rate

5. ICU Admissions

6. ICU Admission Source and Service

7. Duration of Mechanical Ventilation

8. ICU Mortality Rate – Unadjusted

9. Hospital Mortality Rate – Adjusted

10. ICU Admissions for Low-Risk Monitoring

11. ICU Census - Hourly Utilization

Reports

Dashboards

Value of this data?

INFORMATIONOVERLOAD

orLACK OF

INFORMATION

2010©2011 MFMER | slide-34

1985

DashboardsThe Stability and Workload Index for Transfer (SWIFT score)

Daily APACHE

Dashboards: administrative and clinical

©2011 MFMER | slide-36

EXAMPLE

Anti MicrobialAB admin YesCultures Taken YesSource Control No

O2 0.68.0 ETT Easy IMV VC

Fluid Bolus 4LNE 0.80aVP 0.03

RR 28SpO2 92PaO2/FiO2 200

HR 118 SRMAP 65ST ∆ No

ToC 38.9WBC 15

IHDCCFHypertension

Surgery-Stent

ObeseCOPDSmoker

Alcoholism

CVS

Renal

CNS

Respiratory

Hematologic

GIT

Sepsis

EKG NormalECHO N/ATroponin 0.02

CXR InfiltratepH 7.28pCO2 55PO2 80HCO3 24

HB 10g/dLBlood Loss 0 mlHct 0.27X Match DoneIV Access 2x20G

Possible SepsisMAP

<65HR

>90T

>38.4WBC

>12

Syndrome Advisory

Treatment GoalsMAP

>65SvO2

>70AB

<1hr

StatusCVP

10Lactate

3.0SvO2

68AB GivenYesX-Match

Done

Date SourceOrganism

03.08 BloodPending

03.08 BALPending

03.08 UrinePending

Name: Age: Source:

AWARE

Sniffers

Sniffers – rule based DSS

Notable sniffers

Herasevich V, Pieper MS, Pulido J, et al. Enrollment into a time sensitive clinical study in the critical care setting: results from computerized septic shock sniffer implementation. J Am Med Inform Assoc 2011. (PMID: 21508415)

Herasevich V, Tsapenko M, Kojicic M, et al. Limiting ventilator-induced lung injury through individual electronic medical record surveillance. Crit Care Med 2011;39(1):34-39. (PMID: 20959788)

Herasevich V, Yilmaz M, Khan H, et al. Validation of an electronic surveillance system for acute lung injury. Intensive Care Med 2009;35(6):1018-1023. (PMID: 19280175)

ALI VILI Septic Shock

Data retrieval for research

Olmsted county

Olmsted county

admission

METRICdatamart

Clinical studies

• Enrollment to time sensitive trials

• Retrospective studies for Quality Improvement an research

Future

Facilitate 3 distinct data use scenarios

• Point of care novel user interfaces, alerts and decision supports

• Reporting

• Research

Team

/co

nta

cts

Data integrity Greg Wilson, RRT

Clinical leadership Daryl Kor, MD

Medical informatics leadership Vitaly Herasevich, MD, PhD

ICU/OR datamart programming lead

Man Li, MD

OR datamart programming

Nageswar Madde

SAS programmingAndrew Hanson

Clinical ExpertiseArun Subramanian, MBBS

Clinical Expertise Brian Pickering, MD

Vision/Mentoring Ognjen Gajic, MD

Data requestsRahul Kashyap, MBBS

2 FTE

Department ChairBradly J. Narr, MD

When the machines that men invented over time would now even function: what pleasant life this would be!

Kurt Tucholsky, German writer and satirist,

1890-1935

©2011 MFMER | slide-47

herasevich.vitaly@mayo.edu

http://mayoresearch.mayo.edu/mayo/research/clinical-informatics-in-intensive-care/